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Record W4387809717 · doi:10.3389/frcha.2023.1206922

The DREAM BIG project as a model for harmonizing early measures of parental care and parent-child interactions across epidemiological cohorts

2023· article· en· W4387809717 on OpenAlexafffund
Eszter Székely, David P. Laplante, Henning Tiemeier, Jonathan Evans, Rebecca M. Pearson, Mona Bekkhus, Marian J. Bakermans‐Kranenburg, Marinus H. van IJzendoorn, Ashley Wazana

Bibliographic record

VenueFrontiers in Child and Adolescent Psychiatry · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill UniversityJewish General Hospital
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMarch of Dimes Foundation
KeywordsMental healthPsychologyPsychopathologyDevelopmental psychopathologyDevelopmental psychologyDreamChild psychopathologyChild developmentSample (material)Early childhoodClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Parenting is a key contributor to child development. The effects of parenting, however, also depend on child characteristics, including genetic factors. A more complete appraisal of the role of parenting thus requires a comprehensive developmental model which explores questions about parenting behavior, child susceptibility to parenting, and child psychopathology. Moving forward, we need to not only be concerned about sample sizes that limit testing of comprehensive models but also the need to replicate findings across multiple settings and samples. A consortium which harmonises key measures offers the opportunity to examine these questions. The Developmental Research in Environmental Adversity, Mental health, BIological susceptibility and Gender (DREAM BIG) consortium includes six international longitudinal prospective birth cohorts to explore the early life origins of major psychiatric disorders in childhood. Here, we will provide a brief overview of parental care research, methodological limitations, and two exciting recent attempts (i.e., the DREAM BIG consortium and the CATS-project), that address key methodological challenges.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.330
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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